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Record W7067488457

In Memoriam: James D Rising

2024· article· en· W7067488457 on OpenAlexaboutno aff

Bibliographic record

VenueDigital Commons - University of South Florida (University of South Florida) · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Bioinformatics, and Biomedical Research
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)Work (physics)Perspective (graphical)Natural (archaeology)Context (archaeology)
DOInot available

Abstract

fetched live from OpenAlex

JAMES DAVID RISING-Jim to everyonedied in Toronto on 13 March 2018, as a result of complications following surgery.He packed more birding, ornithological research and writing, teaching, and mentoring into his 75 years of life than most of us can hope to do and will be missed greatly by many, many friends and students, as well as his family.Born in Kansas City in 1942, Jim was a keen birder from an early age.A member of the American Ornithologist's Union (AOU, now AOS) at 14, he was active with the Burroughs Bird Club in Kansas City, participating in the city's Christmas Bird Count in the 1950s and 1960s.He also joined the Kansas, Cooper and Wilson Ornithological Societies in his teens, which surely presaged a career in ornithology.Jim completed a B.A. in Zoology at the University of Kansas (KU) in 1964.While there, he began working with Richard Johnston at the KU Natural History Museum.Johnston eventually agreed to be Jim's Ph.D. supervisor-as long as he promised to go elsewhere for a post-doc.Kansas was the perfect place for his doctoral project, however, which was on the hybridization of Bullock's and-Baltimore Orioles in the Great Plains-a subject

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.029
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.022
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0060.002
Scholarly communication0.0070.002
Open science0.0020.004
Research integrity0.0080.020
Insufficient payload (model declined to judge)0.0290.019

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.219
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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